Image segmentation is an essential issue in image description and classification. Currently, in many real applications, segmentation is still mainly manual or strongly supervised by a human expert, which makes it irreproducible and deteriorating. Moreover, there are many uncertainties and vagueness in images, which crisp clustering and even Type-1 fuzzy clustering could not handle. Hence, Type-...

Zoning the pollution of a river may be the first or even the most important step in water quality management. In order to resolve its pollution, fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates mutiple parameters&#10 &#10In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy cluster...

this paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (fpso) and fuzzy c-means (fcm) algorithms, to solve the fuzzyclustering problem, especially for large sizes. when the problem becomes large, thefcm algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. the pso algorithm does find ago...

the objective of this investigation was to evaluate the magnitude of g × e interaction effects on durum wheat grain yield and to identify superior genotypes adapted to the test environments. twenty improved durum wheat genotypes were tested in five locations over three growing seasons. combined anova indicated that the effect of year (y) was significant and that of the location (l) was not, but...

with rapid development in information gathering technologies and access to large amounts of data, we always require methods for data analyzing and extracting useful information from large raw dataset and data mining is an important method for solving this problem. clustering analysis as the most commonly used function of data mining, has attracted many researchers in computer science. because o...

the wisdom of crowds, an innovative theory described in social science, claims that the aggregate decisions made by a group will often be better than those of its individual members if the four fundamental criteria of this theory are satisfied. this theory used for in clustering problems. previous researches showed that this theory can significantly increase the stability and performance of lea...

background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. we have presented two ordinal–variables clustering exampl...